In the wake of digital transformation, the real opportunity does not lie in reskilling people to do tasks that could be automated in the future, but in equipping them with the capability to solve human problems.
By Anton Herbst, group strategy director at Tarsus Technology Group.
Digital technology has changed how we live and work in profound ways over the past 30 years. Software has eaten the world; combined with ubiquitous connectivity, software algorithms have automated many of the tasks and processes that human workers once used to do. And this is just the beginning of a significant shift in the workforce that will unfold over the next 20 years.
Smarter artificial intelligence (AI), big data and the proliferation of robots and Internet-connected sensors will drive automation in every industry at an exponential rate. A McKinsey analysis of 2000 work activities across more than 800 occupations shows that roughly half the activities (not jobs) carried out by workers could be automated.
This reality is the source of much angst for think tanks, policymakers and workers, with many forecasting mass job losses because of automation in the years to come. The World Economic Forum (WEF), for example, cites stats indicating the loss of 236 million jobs in China, 120 million in India and 73 million in the US by 2030.
To address the possibility of mass job losses, many organisations talk about ‘reskilling’ or ‘upskilling people’. But this response is likely to be inadequate, when you reflect on what it actually means to develop a ‘skill’ in the context of the workplace – it’s usually about building the ability to fulfil a particular task or process as efficiently as possible.
Production-line thinking
This reflects the production-line thinking of the industrial age – getting people to make as many widgets on an assembly line or resolve as many inbound calls in a call centre as they possibly can in an hour. Here’s the problem – these are the sort of repetitive, standardised, contextual and integrated tasks at which machines and software excel.
While you can teach people such skills, humans simply cannot keep up with the pace at which technologies such as robotic process automation and advanced robots are advancing. And once a machine or algorithm has been taught to do a task like populating a database from data captured in a scanned PDF, it will be able do so quicker, with more consistency, and more accurately than a human.
If we look at labour productivity from 1950 to now, in 70 years, we’ve managed to double productivity. If you look at the same time frame the increase in the capability of technology is about 8 million times. There is a massive gap opening between the human learning process and the growth in machine-driven productivity.
So, a strategy of merely teaching people new skills to do tasks that machines cannot yet do cheaply or reliably is not an answer to the challenge of job losses to automation. It is also not an answer to ensuring an organisation’s competitiveness in the longer term – as most enterprises in an industry drive inefficiencies out of their business via automation, they will converge on a point where their cost base and productivity are comparable.
Thinking about the workforce in a new way
I believe that the answer to both the societal challenges of job losses to automation and to the organisational challenge of competitive differentiation lies in thinking about the workforce in a new way. Rather than treating people as robots to be optimised for productivity and efficiency, leading employers will think about how they can harness their innate human capabilities to build a better business.
When we talk about a capability, we are speaking of traits and aptitudes that are uniquely human and that are not bound to the context of a single task or business process. Some examples are empathy, creativity, critical thinking, leadership, negotiation, and innovation. This is how an organisation delivers the fresh ideas and great experiences that enable it to win in a changing world.
COVID-19 has stressed-tested technology, and shown us where its strengths and limitations are. As we all start to look beyond the pandemic, it is the human touch that will matter more and more. Automation can make an organisation more efficient, but human capability helps it solve human problems. And that’s what will truly matter in the future.